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Name of the project : DISCRET

Type of project (internship / thesis / post-doc / ANR...) : Research projects

Summary: DISCRET aims at demonstrating the possibility to detect and locate, in real-time, unusual or critical situations in urban areas, based on the analysis of cell phone network data. This detection will be complemented with information extracted from social networks (i.e., Twitter in the context of the project). A prototype of a warning platform for security and emergency operators will be implemented. Several recent research works have shown that major events induce locally significant modifications of the amount and nature of cellular network communications. These anomalies, typically concomitant with the unusual event, may be detected and located based on the network of cell phone antennas. Moreover, the early detection and localization of the events, together with the knowledge of the associated communication activity, allow for a more effective retrieval of information from the social networks. That permits to provide elements of description and context for the detected event and, therefore, to increase the value of the information conveyed by the population via channels that are not explicitly conceived for alerting purposes.

Name of supervisor(s) : Eric Gaume et Angelo Furno (Ifsttar), Tamara Tosic et Zsbigniev Smoreda (Orange), Babiga Birregah (UTT)

Start and end of the project : 2020-01-01 - 2021-06-30

Duration : 18 months

Additional financing (if aaplicable) Orange